Considering the potential of shaded coffee plantations mixed with natural vegetation for promoting biodiversity conservation, this project assessed the utility of multi-date Landsat Thematic Mapper (TM) satellite imagery for the characterization of natural vegetation versus coffee plantations in western El Salvador. For assembling a multi-temporal Landsat TM data set, we applied a regression analysis model to remove cloud cover and cloud shadows. Then, through a hybrid classification approach, a nine-class land use/land cover (LULC) map was generated.

Study on household food security is very essential now that Nigeria is currently facing the problem of food crisis. This study presents findings on household food security in the North Central Nigeria (NCN). The first objective was to review and highlight the commonly used measures of households' food security with their pros and cons; second, to determine the food security status of households; and third, to analyse the determinants of household food security status in the study area.

Change detection is one of the primary applications of remote-sensing data, and many techniques have been developed during the past three decades. Although frequently criticized and despite many alternatives, due to its simplicity and intuitive manner, post-classification change detection still remains one of the most applied techniques. Many studies in the field of change detection analysis acknowledge, for instance, the impact of misregistration, inconsistencies in classification schemes or differences in methods for image interpretation.